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dc.contributor.authorMozerov, Mikhail-
dc.contributor.authorRius, Ignasi-
dc.contributor.authorRoca, F. Xavier-
dc.contributor.authorGonzàlez, Jordi-
dc.date.accessioned2010-12-17T07:37:35Z-
dc.date.available2010-12-17T07:37:35Z-
dc.date.issued2006-
dc.identifier.citation28th Annual Symposium of the German Association for Pattern Recognition: pp. 485-494 (2006)-
dc.identifier.isbn9783540444121-
dc.identifier.urihttp://hdl.handle.net/10261/30361-
dc.descriptionAnnual Symposium of the German Association for Pattern Recognition (DAGM), 2006, Berlin (Germany)-
dc.description.abstractThis work solves the problem of synchronizing pre-recorded human motion sequences, which show different speeds and accelerations, by using a novel dense matching algorithm. The approach is based on the dynamic programming principle that allows finding an optimal solution very fast. Additionally, an optimal sequence is automatically selected from the input data set to be a time scale pattern for all other sequences. The synchronized motion sequences are used to learn a model of human motion for action recognition and full-body tracking purposes.-
dc.description.sponsorshipThis work was supported by the project 'Integration of robust perception, learning, and navigation systems in mobile robotics' (J-0929).-
dc.language.isoeng-
dc.publisherSpringer Nature-
dc.rightsopenAccess-
dc.subjectPattern recognition: Computer vision-
dc.subjectComputer vision-
dc.title3D human motion sequences synchronization using dense matching algorithm-
dc.typecomunicación de congreso-
dc.identifier.doi10.1007/11861898_49-
dc.description.peerreviewedPeer Reviewed-
dc.type.coarhttp://purl.org/coar/resource_type/c_5794es_ES
item.fulltextWith Fulltext-
item.languageiso639-1en-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.openairetypecomunicación de congreso-
item.cerifentitytypePublications-
item.grantfulltextopen-
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